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Monte Carlo Complexity of Parametric Integration

  • The Monte Carlo complexity of computing integrals depending on a parameter is analyzed for smooth integrands. An optimal algorithm is developed on the basis of a multigrid variance reduction technique. The complexity analysis implies that our algorithm attains a higher convergence rate than any deterministic algorithm. Moreover, because of savings due to computation on multiple grids, this rate is also higher than that of previously developed Monte Carlo algorithms for parametric integration.

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Metadaten
Author:Stefan Heinrich, Eugène Sindambiwe
URN (permanent link):urn:nbn:de:hbz:386-kluedo-49437
Serie (Series number):Interner Bericht des Fachbereich Informatik (297)
Document Type:Report
Language of publication:English
Publication Date:2017/10/25
Year of Publication:1998
Publishing Institute:Technische Universität Kaiserslautern
Date of the Publication (Server):2017/10/25
Number of page:21
Faculties / Organisational entities:Fachbereich Informatik
DDC-Cassification:0 Allgemeines, Informatik, Informationswissenschaft / 004 Informatik
Licence (German):Creative Commons 4.0 - Namensnennung, nicht kommerziell, keine Bearbeitung (CC BY-NC-ND 4.0)